An R package for the spectral and spatial analysis of color patterns

About

pavo is an R package developed with the goal of establishing a flexible and integrated workflow for working with spectral and spatial colour data. It includes functions that take advantage of new data classes to work seamlessly from importing raw spectra and images, to visualisation and analysis. It provides flexible ways to input spectral data from a variety of equipment manufacturers, process these data, extract variables, and produce publication-quality figures.

download files from GitHub and install using $R CMD INSTALL or, from within R:

install.packages(path, type='source', repos=NULL)

News

pavo 2.1.0

NEW FEATURES AND POTENTIALLY BREAKING CHANGES

added the argument reclass to procimg(), which allows users to interactively
correct areas within images that have been misclassified

added the rod sensitivity of Canis familiaris

peakshape() uses a completely different algorithm to find the FWHM. It now
works as expected for spectra with multiple peaks. See PR #137 for a detailed
overview of the changes.

data used internally by pavo (bgandilum, transmissiondata, ttvertex, vissyst) is no longer exposed to users

MINOR FEATURES AND BUG FIXES

new functions is.vismodel() and is.colspace() are exported to test whether an object is of class vismodel or colspace, respectively

fixed a bug where images would sometimes be wrongly detected as user-classified in as.rimg()

the UV-sensitive cone is now only always named "u", even for VS species (such as pfowl and avg.v in vismodel() and sensdata()). This removes an unnecessary but harmless warning when colspace() was used to place quantum catches of such species in the tetrahedral colour space.

the achro argument in coldist() has been changed for achromatic to
better match the arguments from vismodel(). Older scripts that use achro
should not be affected and still work as before.

the package imager is no longer a dependency, and is only loaded if using some
features of procimg().

the package mapproj is no longer a dependency, and is only loaded if using
projplot().

added the argument labels.stack to plot.rspec, which allows the use of
custom spectra labels in stacked plots.

users now receive a warning when interpolating beyond the limits of the data using as.rspec, and can control the behaviour with the new argument exceed.limits.

all deprecated functions and arguments have now been fully removed.

as.rspec() now accepts both numeric and character vectors to identify the wavelength column using whichwl (eg. whichwl = "wl").

Reference images in classify() can now be specified using either a numeric vector (to identify by image position in a list) or character vector (to identify by image name).

fixed a bug in aggspec() when wavelength column was previously removed by the user.

fixed a bug where cocplot() would failed whenever type graphical parameter was specified.

spec2rgb() has been simplified to rely more on vismodel(). As a result, output values may be slightly different but upon testing, we found that differences between the old and the new version were barely noticeable.

the vignette have been split into three smaller parts, which should help new users to get started with pavo

numerous under-the-hood changes for stability and speed, with thanks to
three reviewers and an associate editor at MEE.

pavo 2.0.0

NEW FEATURES

image-based workflow for the combined analysis of colour and pattern geometry

MINOR FEATURES AND BUG FIXES

Carotenoid chroma (S9) in summary.rspec() has been fixed to (R700 - R450)/R700.
This gives the same result as before but with a flipped sign, and better reflects
the original formula in the literature.

cieLAB values have been rescaled, and are expressed in the more standard range:
L [0,100], ab [-128,127]

getspec() has an additional argument ignore.case set to TRUE by default
to ignore case in file extension matching

fix a bug where getspec() would sometimes fail with files including numbers in
scientific format

add a new option in tetraplot() to add cone names (u,s,m,l)

pavo 1.4.0

NEW FEATURES

getspec() can now read OceanOptics .ProcSpec files

added the visual system of Ctenophorus ornatus, the (trichromatic) ornate dragon lizard

MAJOR CHANGES

getspecf() (and the argument fast = TRUE in getspec()) have been deprecated

summary.rspec() returned incorrect values for S7. If you use S7, please re-run
your analyses

pavo 1.2.0

MAJOR CHANGES

MINOR FEATURES AND BUG FIXES

vignettes have been amalgamated & the single, main vignette is now up-to-date

added more informative labels for the segment analysis plot

pavo 1.1.0

NEW FUNCTIONS

segspace() replaces the deprecated segclass(), and is accessed via the colspace() argument space = 'segment'. The results of segspace()
are also now compatible with coldist() for the estimation of Euclidean colour-distances.

segplot() is a plot for Endler's (1990) segment analysis, and is accessed — along with all other 2d plots — via plot.colspace()

MINOR FEATURES AND BUG FIXES

the use of relative quantum catches is now optional in the categorical colorspace (though still produces a warning), for greater flexibility

updated several functions to work when rspec object has only one spectrum

fixed bug in voloverlap where interactive plots would result in error

fixed incorrect labels in the maxwell triangle plot

fixed a bug in as.rspec() in which lim was not applied when interpolate = FALSE

fixed bug in aggplot() which resulted in error when using lty, lwd arguments

warning if ocular media is being used in both vismodel() and sensmodel()

added an 'all' option to the achromatic argument in vismodel()

added the ability to calculate dL for cielab models in coldist()

added some more informative messages and warnings

pavo 1.0

See vignette for detailed description of changes.

MAJOR CHANGES

coldist() arguments have been changed. Now the empirically estimated value for the Weber fraction must be entered, instead of the noise-to-signal ratio. The noise-to-signal ratio is then calculated based on the empirically estimated Weber fraction for the reference cone type, and applied to the remaining cone types. This should avoid confusion between empirically estimated values for the Weber fraction and the noise-to-signal ratio, which are currently prevalent in the literature.

coldist() now has an additional argument, weber.achro, so that the value for the Weber fraction to be used to calculate achromatic contrast can be input independently of the cone ratios.

tcs() is deprecated, replaced by colspace().

NEW FUNCTIONS

colspace() replaces tcs() and introduces several new colorspaces

plot() methods for several colspace() outputs, including a static tetrahedral colorspace